Customer Trust in AI-Enabled Digital Marketing: Evidence from India’s Real Estate Sector

Abstract

Artificial intelligence (AI) has become a defining force in the evolution of digital marketing, reshaping the way organizations interact with and influence customers. From chatbots and recommendation systems to predictive analytics and automated personalization, AI-driven tools offer firms unprecedented opportunities to engage customers effectively. However, alongside these opportunities lies a critical challenge customer trust. In industries like real estate, where purchase decisions are high-value and high-risk, customer trust becomes not just desirable but indispensable for the success of AI-enabled digital marketing initiatives. This paper investigates the dynamics of customer trust in AI-enabled digital marketing in the context of India’s real estate sector, with a focus on the National Capital Region (NCR). Drawing on trust theory and the Technology Acceptance Model (TAM), the study conceptualizes trust as a central construct influenced by AI-enabled personalization, responsiveness, transparency, and data privacy concerns. Using a survey of 400 real estate customers, the study employs structural equation modeling (SEM) to examine how trust shapes customer engagement and purchase intentions. Findings indicate that while AI-enabled personalization and responsiveness significantly enhance trust, concerns regarding privacy and data security can undermine it. Moreover, customer trust acts as a mediator between AI-driven marketing practices and engagement outcomes. The study contributes to literature by positioning trust as a critical enabler of AI adoption in marketing, particularly in emerging market contexts. Practically, it highlights that the effectiveness of AI in digital marketing depends not only on technological sophistication but also on firms’ ability to inspire and sustain customer trust.